What Is Big Data Storage?

When you think of data storage, imagine a little box with a handle, like one of those old-fashioned film canisters. Data storage has changed a lot in the last few years. That's because big data is here to stay, and it's only getting bigger. Companies are collecting more and more information about their customers, employees and products, and they're not just keeping it in a box anymore. They're storing it online and using it to make better decisions. Big data storage is a way of storing information so that it can be accessed easily and quickly by applications and services working on big data. Big data storage enables the storage and sorting of big data so that it can easily be accessed, used and processed by applications and services working on big data. It also scales as required by expanding its capacity or adding more servers to support more users accessing the same amount of data simultaneously. Big data storage, a.k.a. "sprawl," is the storage of data that's so big it needs to be stored somewhere else. It's not just about how much space you need, however. It's also about how fast you need to get at the data to make sense of it. Big data storage usually involves clusters of servers connected via a network, which can be accessed by multiple users simultaneously (to read or write) without slowing down the system as a whole too much. The most popular way to store big data is called "NoSQL" ("Not Only SQL"), which means that instead of using traditional SQL databases like MySQL or Oracle, you also use something more flexible (and scalable). These systems are typically open source and often based on object stores like S3 or Azure Blob Storage.

By TechDogs Editorial Team

Related Terms by Storage

Sentiment Analysis

Sentiment analysis is a lot like having the ability to discern minds, except it's done with computers. Opinion mining is a data mining subfield that utilizes unstructured text analysis to gauge consumer sentiment toward a brand, individual, or concept. Sentiment analysis is a technique for gleaning emotional data from online sources using NLP, computational linguistics, and text analysis. Social media sites and other online forums where users post their thoughts and observations on various subjects are familiar places to find this data. Sentiment analysis uses complex algorithms and machine learning methods to identify a person's opinion's positive, negative, or neutral nature. As a bonus, it can determine whether the text is joyful, sad, angry, or anxious, as well as other emotions. The results of this analysis can be used to calculate the extent to which the public approves or disapproves of various brands, individuals, and concepts. Knowing the thoughts and preferences of customers can be invaluable to companies and organizations. A business may employ mood analysis to monitor customer feedback via social media and use the results to improve its offerings. The material's polarity in its context can also be revealed through sentiment analysis. It can tell you how people feel about a subject or entity and what it is about that subject or entity that people like or dislike. Sentiment analysis can show, for instance, that consumers have a generally positive attitude toward a given brand but a negative attitude toward its customer service. To sum up, sentiment analysis is a subfield of data mining that assesses consumer reaction to a brand, individual, or concept by examining written language. It's like having the ability to read thoughts, only this time, and it's accomplished through complex mathematical formulas stored in a computer. Sentiment analysis, or opinion mining, is a method for gleaning and analyzing biased data from online sources, such as social media and blogs. Data analysis can reveal the contextual polarity of information and provide quantitative estimates of the public's feelings or responses to specific goods, people, or ideas.

Self-Provisioning

If you're like most people, you're always looking for ways to get out of work. So when we heard about self-provisioning—the ability to set up services and applications by yourself without the help of a dedicated IT specialist or service provider—we were all over it. It's like having your server, except that instead of having to buy your server, pay for its maintenance, and hire an IT person to manage it when things go wrong, you sign up with a cloud provider who has already done everything for you. Moreover, they'll even let you use their servers for free! So if you have ever wanted to launch your website but didn't want to take on the burden of managing it yourself, or if you've been dreaming of starting an online business but didn't want to spend all that money on servers and software licenses well, now's your chance! Self-provisioning is excellent, but the self-de-provisioning part is even more significant. Provisioning is like getting a massage—you know what you want and are in charge of getting it. Deprovisioning is like getting a haircut—it's a little more complicated than telling someone what to do. It requires much attention to detail and technical skill to ensure you're not cutting off any substantial parts of yourself in your zeal to be smooth and sleek. We don't want you to be soft and elegant! We want you to be well-groomed! So here are some tips for taking care of yourself by taking care of your resources. Always deprovision after using a resource so that others can use it when they need it later. Only do something once you've found another that does what that other one did for you (and then de-provision the old one).

Secure Hash Algorithm (SHA)

Secure Hash Algorithm is a set of algorithms developed by the National Institutes of Standards and Technology and other government and private parties. Cryptographic hashes (or checksums) have been used for electronic signatures and file integrity for decades. However, these functions have evolved to address some of the cybersecurity challenges of the 21st century. The NIST has developed a set of secure hashing algorithms that act as a global framework for encryption and data management systems. The initial instance of the Secure hash Algorithm (SHA) was in 1993. It was a 16-bit hashing algorithm and is known as SHA-0. The successor to SHA-0, SHA-1, was released in 1995 and featured 32-bit hashing. Eventually, the next version of SHA was developed in 2002, and it is known as SHA-2. SHA-2 differs from its predecessors because it can generate hashes of different sizes. The whole family of secure hash algorithms goes by the name SHA. SHA-3, or Keccak or KECCAK, is a family of cryptographic hash functions designed by Guido Bertoni, Joan Daemen, Michaël Peeters, and Gilles Van Assche. SHA-3 competition to develop a new secure hash algorithm was held by the United States National Security Agency (NSA) in 2007. To be a super safe and fast hashing algorithm, SHA3 was developed from this contest. The evolution of cybersecurity has led to the development of several "secure hash algorithms." Security is a crucial concern for businesses and individuals in today's digital world. As a result, many types of encryption have been developed to protect data in various scenarios. One of these is hash algorithms. All secure hash algorithms are part of new encryption standards to keep sensitive data safe and prevent different types of attacks. These algorithms use advanced mathematical formulas so that anyone who tries to decode them will get an error message that they aren't expected in regular operation.

Trending Definitions

UTF-8

When it comes to encoding characters, UTF-8 is your go-to. It's a relatively new code convention for encoding various characters, and it's the character that has his identity and a reference for a wide variety of programming languages and devices, including computers and mobile devices. The protocol helps to standardize the display of letters, numbers and other characters in your daily life, and those are just some of its benefits! UTF-8 was developed from 1985–to 1987 when the Internet was multiplying, and there was a need to standardize character encoding to facilitate communication between different languages. The original intent of UTF-8 was to enable communication between other languages. There were many different character sets in use, making communication difficult. The best-known example is the Chinese character set, which was in the very early stages of its current evolution. Chinese characters at the time would have been unintelligible to speakers of most other languages. UTF-8 is a way to store information on computers. It takes the place of an older convention called the American Standard Code for Information Interchange (ASCII). ASCII handles all the characters necessary for English text, but UTF-8 handles more diverse sets of symbols for other languages that do not use the English language or Roman alphabet. UTF-8 is considered backward-compatible with ASCII. With UTF-8, a single device can display various characters from different languages and use a single piece of code to search for multiple keywords with other diacritical marks. In addition to the increased versatility of UTF-8, it also offers ease of implementation. According to software engineers and developers, one of the most challenging aspects of this encoding technique is modifying their code to conform to ASCII standards. These difficulties are handled by using UTF-8. ASCII is old and busted, but UTF-8 is the new thing! ASCII was a great start, but the world has changed. There are more people, languages and devices than ever before, so we need a more inclusive system to meet the needs of this evolving world. UTF-8 is that system.

Supply Chain Visibility (SCV)

Understanding your supply network better is a must. Like a crystal ball, it reveals the precise location of a company's goods at all times, from when they depart the factory to when they are delivered to the client. Comparable to seeing all the meaty details of the supply network behind the scenes. Well, OK, but how does it work in detail? However, Supply Chain Visibility (SCV) is all about using technology to track information and products as they move from point to point in the supply chain. Playing "Where's Waldo?" with shipping containers, pallets, and cars. You're not looking for Waldo; you're tracking manufacturing schedules, shipping times, and inventory levels. SCV requires a system that can reliably collect and process this information in real time. Electronic data interchange (EDI), a global positioning system (GPS), and radio frequency identification (RFID) all play a role in this context. These developments allow businesses to track their products in transit and share that information with suppliers, customers, and other stakeholders. Then, why should we put so much stock in SCV? At the outset, it helps corporate leaders make better choices. Businesses can improve efficiency and save money by keeping tabs on inventory and shipping periods in real time. In addition, it helps companies better respond to the needs of their customers. A company with a high SCV can accurately estimate the delivery time of a customer's purchase. SCV's objectives go far beyond simply increasing productivity and making customers happy. There is also an emphasis on minimizing danger. Monitoring the movement of products throughout the supply chain can help businesses identify possible bottlenecks and address them before they worsen. They can identify security risks, such as theft or counterfeiting, and take corrective action. For businesses serious about growth, SCV is an invaluable tool. This insight is like flourishing a magic wand before you, revealing the future so you can prepare for it. If a business has access to the appropriate resources and personnel, SCV can be used to increase output and improve customer service.